picovoice
DeepSpeech
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picovoice | DeepSpeech | |
---|---|---|
13 | 67 | |
497 | 24,212 | |
6.2% | 1.2% | |
8.9 | 0.0 | |
6 days ago | 2 months ago | |
Python | C++ | |
Apache License 2.0 | Mozilla Public License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
picovoice
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Speech Recognition in Unity: Adding Voice Input
Download the Picovoice Unity package
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Speech Recognition using Arduino Nano 33
Picovoice Platform GitHub Repository
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Speech Recognition with SwiftUI
Below are some useful resources: Open-source code Picovoice Platform SDK Picovoice website
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Speech Recognition with STM32: Building hands-free voice experiences
git clone --recurse-submodules \ https://github.com/Picovoice/picovoice.git
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Day 20: On-device Voice Assistant with Flutter
You can use the demo code we open-sourced. It includes wake word and context files, so you can start with them.
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Day 7: Making Cool Raspberry Pi Projects even Cooler with Voice AI (2/4)
You can check out the GitHub repo to see more open-source demos
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Offline Voice Assistant on a Microcontroller with 192KB RAM
Although interestingly enough, the README for the linked repo (https://github.com/Picovoice/picovoice) states that "The SDK is licensed under Apache 2.0 and available on GitHub to encourage independent benchmarking and integration testing." While source isn't provided and only compiled binaries are provided, that should give you permission to flip some bits to skip a license check.
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Voice processing in Embedded Systems
Checkout https://github.com/Picovoice/picovoice I saw it on an article from before and it seemed easy to get started on.
- Voice Control App
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Clock app controlled with offline voice recognition (Tutorial + article in comments)
Check out an article I wrote about it and the source code
DeepSpeech
- Common Voice
- Ask HN: Speech to text models, are they usable yet?
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Looking to recreate a cool AI assistant project with free tools
- [DeepSpeech](https://github.com/mozilla/DeepSpeech) rather than Whisper for offline speech-to-text
I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest way to implement it using free, open-source software. Here's what he used originally, followed by some open source candidates I'm considering but would love feedback and advice before starting: Original Tools: - YoloV8 does the heavy lifting with the object detection - OpenAI Whisper handles voice - GPT-4 handles the “AI” - Google Custom Search Engine handles web browsing - MacOS/iOS handles streaming the video from my iPhone to my Mac - Python for the rest Open Source Alternatives: - [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection - Replacing GPT-4 is still a challenge as I know there are some good open-source LLms like Llama 2, but I don't know how to apply this in the code perhaps in the form of api - [DeepSpeech](https://github.com/mozilla/DeepSpeech) rather than Whisper for offline speech-to-text - [Coqui TTS](https://github.com/coqui-ai/TTS) instead of Whisper for text-to-speech - Browser automation with [Selenium](https://www.selenium.dev/) instead of Google Custom Search - Stream video from phone via RTSP instead of iOS integration - Python for rest of code I'm new to working with tools like OpenCV, DeepSpeech, etc so would love any advice on the best way to replicate the original project in an open source way before I dive in. Are there any good guides or better resources out there? What are some pitfalls to avoid? Any help is much appreciated!
- Speech-to-Text in Real Time
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Linux Mint XFCE
algo assim? https://github.com/mozilla/DeepSpeech
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Are there any secure and free auto transcription software ?
If you're not afraid to get a little technical, you could take a look at mozilla/DeepSpeech (installation & usage docs here).
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Web Speech API is (still) broken on Linux circa 2023
There is a lot of TTS and SST development going on (https://github.com/mozilla/TTS; https://github.com/mozilla/DeepSpeech; https://github.com/common-voice/common-voice). That is the only way they work: Contributions from the wild.
- Deepspeech /common voice.
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Mozilla Launches Responsible AI Challenge
Mozilla did release DeepSpeech[0] and Firefox Translation[1] (the latter of which they included in Firefox, to offer client-side webpage translations.)
They definitely have fewer resources than OpenAI, and they do not produce SOTA research (their publications have plummeted to 1/year anyway[2]). So the only way for them to make progress is to seek government grants or make challenges like these.
This challenge is unlikely to be profitable for the winning team: the expected value of winnings are likely around $1K when taking into account the probability that another team gets a better rank, but ML research projects are often more expensive (recently, Alpaca spent upwards of $600 on computation alone; and of course pretraining large models is much more expensive). So the main gain will be publicity.
[0]: https://github.com/mozilla/deepspeech
[1]: https://github.com/mozilla/firefox-translations/
[2]: https://research.mozilla.org/
What are some alternatives?
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
Kaldi Speech Recognition Toolkit - kaldi-asr/kaldi is the official location of the Kaldi project.
spokestack-python - Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.
NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
rhino - On-device Speech-to-Intent engine powered by deep learning
STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
cheetah - On-device streaming speech-to-text engine powered by deep learning
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
DiscordSpeechBot - A speech-to-text bot for discord with music commands and more using NodeJS. Ideally for controlling your Discord server using voice commands, can also be useful for hearing-impaired people.
PaddleSpeech - Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
Speech-Recognition - Speech Recognition library for adding Voice Commands and Controls to all your applications. Whether you are building web apps, native apps or desktop apps, this technology can be integrated into any system with an internet connection.
dicio-android - Dicio assistant app for Android